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Raapid | Risk Adjustment Provider

RAAPID Takes Medical Coding for Risk Adjustment to the Desired Leap of Accuracy and Profitability

The risk capture platform has emerged as a game-changer in the medical coding space as automation and artificial intelligence have come to replace what were once entirely manual and not AI-driven processes.

LOUISVILLE, Ky., May 16, 2022 ( – The RAAPID risk capture platform is actively taking medical coding to the desired leap of accuracy and profitability with its unique usage of artificial intelligence technology. As the world’s first personalized AI assistant for risk capture, RAAPID is helping accelerate the already rapidly growing trend of healthcare institutions leveraging AI to improve coders’ productivity, efficiency, and impact on the overall return on investment (ROI).

As medical coders become increasingly important to payers, providers, and hospitals, the usage of AI to improve daily operations has also become more prevalent. As medical coders work to extract patient data to derive accurate Risk scores, there are a few common challenges that they face on a consistent basis.

The primary dilemma coders face is the time-consuming process of chart review to identify the right codes for unstructured data in free-form text. When searching for verbatims within medical dictionaries, coders will often have to conduct multiple searches to find the appropriate codes. AI enhances this process, helping medical coders find appropriate codes with fewer searches in the majority of instances. This means accurate codes and lesser Chart review timings.

The rising demand for coders to process as many charts as possible is not helped by the fact that the number of medical codes is constantly increasing. If anything, this combination can easily lead to missed revenue and costly compliance mistakes for under-equipped healthcare institutions. AI assistants prevent these shortcomings by automatically flagging a human error, recommending a solution, and informing coders of the differences resulting from said solution.

Without question, medical coding procedures automated by AI are becoming the industry standard
in the medical sector, especially since manual medical coding processes have been proven to be time-consuming, costly, and error-prone.

Because of this new standard, solutions such as RAAPID’s AI-driven risk capture platform have emerged as game-changers in the medical coding space. By providing healthcare, insurance, and technology businesses with AI-driven solutions that are smarter, faster, and more accurate, the RAAPID platform is able to reimagine risk adjustment and suit any organization’s needs, regardless of size or specialty.

RAAPID begins by collecting and organizing all relevant clinical documents, including unstructured notes, before converting all scanned images into text format. NLP technology is then used to extract clinical entities. The platform then utilizes patented knowledge graphs and user-adjusted custom rules to identify the entity relationships. After the code validation phase, a final risk score is calculated based on complete, compliant, and accurate codes (International Classification of Diseases 10 and HCC).

To learn more about how RAAPID can help, please visit

With a comprehensive workforce of over 500 members who are industry veterans, based out of India and the U.S., RAAPID’s pedigree is built upon Trust, Tech Competence, Stability and Tech Innovation.

Healthcare doesn’t stop at 5 o’clock. Neither do we. We know this because it has been close to a decade now. We want your organization to be successful and have accurate reports when you need them. That’s why we make patient service a priority and ensure our technology stays up-to-date to avoid errors entirely.

Every organization is unique and deserves personalized AI solutions, and RAAPID is a completely integrated, AI-powered disease understanding and extracting engine that operates on any patient data—including the free text, and unstructured content—to capture the complete risk of the patients.

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Source: RAAPID